OBO Foundry dashboard analysis

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/tmp/ipykernel_604/4293058459.py:21: FutureWarning:

The `inplace` parameter in pandas.Categorical.reorder_categories is deprecated and will be removed in a future version. Reordering categories will always return a new Categorical object.

Ontologies by number of axioms

Ontologies by number of classes

Ontologies by how many ontologies use it

Different serialisations used

RDF/XML Syntax    5
Name: syntax, dtype: int64

Breakdown of used Axiom Types

	count	mean	std	min	25%	50%	75%	max
AnnotationAssertion	5	101597.0	160052.701122	2.0	8675.0	10773.0	112828.0	375707.0
Declaration	5	11844.2	13661.893489	2.0	1989.0	5628.0	19437.0	32165.0
EquivalentClasses	5	3478.2	3415.438654	1.0	584.0	2842.0	6196.0	7768.0
SubAnnotationPropertyOf	3	9.4	16.334014	0.0	0.0	1.0	8.0	38.0
SubClassOf	3	13809.0	20472.859827	0.0	0.0	1167.0	21193.0	46685.0
SubPropertyChainOf	2	1.6	3.049590	0.0	0.0	0.0	1.0	7.0
DisjointClasses	1	15.6	34.882660	0.0	0.0	0.0	0.0	78.0
SubObjectPropertyOf	1	0.8	1.788854	0.0	0.0	0.0	0.0	4.0
SymmetricObjectProperty	1	0.2	0.447214	0.0	0.0	0.0	0.0	1.0

Breakdown of used OWL Class Expression constructs

	count	mean	std	min	25%	50%	75%	max
Class	5	51784.6	65273.674661	3.0	6184.0	14550.0	88806.0	149380.0
ObjectSomeValuesFrom	5	8784.2	10113.238512	1.0	1151.0	3257.0	18663.0	20849.0
ObjectIntersectionOf	4	3890.2	3820.952656	0.0	717.0	2926.0	7754.0	8054.0
ObjectUnionOf	2	12.4	20.803846	0.0	0.0	0.0	14.0	48.0

OBO Score (Experimental)

	ontology	score	score_dash	score_impact
1	hp	0.560	0.800	0.4
2	maxo	0.531	0.727	0.4
0	ecto	0.458	0.844	0.2
3	mondo	0.389	0.973	0.0
4	tmp	0.113	0.282	0.0

OBO Score Summary

	count	mean	std	min	25%	50%	75%	max
score	5.0	0.4102	0.178952	0.113	0.389	0.458	0.531	0.560
score_dash	5.0	0.7252	0.263412	0.282	0.727	0.800	0.844	0.973
score_impact	5.0	0.2000	0.200000	0.000	0.000	0.200	0.400	0.400

OBO dependency graph